Lending Club Profiling Report

Dataset statistics

Number of variables	34
Number of observations	107843
Missing cells	188505
Missing cells (%)	5.1%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	27.3 MiB
Average record size in memory	265.0 B

Variable types

Numeric	16
Boolean	1
Unsupported	1
Categorical	16

Alerts

`application_type` has constant value "Individual"	Constant
`desc` has a high cardinality: 38454 distinct values	High cardinality
`earliest_cr_line` has a high cardinality: 601 distinct values	High cardinality
`emp_title` has a high cardinality: 68454 distinct values	High cardinality
`title` has a high cardinality: 26875 distinct values	High cardinality
`zip_code` has a high cardinality: 828 distinct values	High cardinality
`df_index` is highly correlated with `id`	High correlation
`id` is highly correlated with `df_index`	High correlation
`fico_range_high` is highly correlated with `fico_range_low`	High correlation
`fico_range_low` is highly correlated with `fico_range_high`	High correlation
`installment` is highly correlated with `loan_amnt`	High correlation
`loan_amnt` is highly correlated with `installment` and 1 other fields	High correlation
`open_acc` is highly correlated with `total_acc`	High correlation
`pub_rec` is highly correlated with `pub_rec_bankruptcies`	High correlation
`pub_rec_bankruptcies` is highly correlated with `pub_rec`	High correlation
`revol_bal` is highly correlated with `loan_amnt`	High correlation
`total_acc` is highly correlated with `open_acc`	High correlation
`df_index` is highly correlated with `id`	High correlation
`id` is highly correlated with `df_index`	High correlation
`fico_range_high` is highly correlated with `fico_range_low`	High correlation
`fico_range_low` is highly correlated with `fico_range_high`	High correlation
`installment` is highly correlated with `loan_amnt`	High correlation
`loan_amnt` is highly correlated with `installment`	High correlation
`open_acc` is highly correlated with `total_acc`	High correlation
`pub_rec` is highly correlated with `pub_rec_bankruptcies`	High correlation
`pub_rec_bankruptcies` is highly correlated with `pub_rec`	High correlation
`total_acc` is highly correlated with `open_acc`	High correlation
`df_index` is highly correlated with `id`	High correlation
`id` is highly correlated with `df_index`	High correlation
`fico_range_high` is highly correlated with `fico_range_low`	High correlation
`fico_range_low` is highly correlated with `fico_range_high`	High correlation
`installment` is highly correlated with `loan_amnt`	High correlation
`loan_amnt` is highly correlated with `installment`	High correlation
`pub_rec` is highly correlated with `pub_rec_bankruptcies`	High correlation
`pub_rec_bankruptcies` is highly correlated with `pub_rec`	High correlation
`application_type` is highly correlated with `grade` and 10 other fields	High correlation
`grade` is highly correlated with `application_type` and 1 other fields	High correlation
`sub_grade` is highly correlated with `application_type` and 2 other fields	High correlation
`issue_d` is highly correlated with `application_type`	High correlation
`Charged off` is highly correlated with `application_type`	High correlation
`home_ownership` is highly correlated with `application_type`	High correlation
`initial_list_status` is highly correlated with `application_type`	High correlation
`purpose` is highly correlated with `application_type`	High correlation
`verification_status` is highly correlated with `application_type`	High correlation
`emp_length` is highly correlated with `application_type`	High correlation
`term` is highly correlated with `application_type` and 1 other fields	High correlation
`addr_state` is highly correlated with `application_type`	High correlation
`df_index` is highly correlated with `id` and 1 other fields	High correlation
`id` is highly correlated with `df_index` and 1 other fields	High correlation
`fico_range_high` is highly correlated with `fico_range_low` and 3 other fields	High correlation
`fico_range_low` is highly correlated with `fico_range_high` and 3 other fields	High correlation
`grade` is highly correlated with `int_rate` and 1 other fields	High correlation
`installment` is highly correlated with `loan_amnt`	High correlation
`int_rate` is highly correlated with `fico_range_high` and 4 other fields	High correlation
`issue_d` is highly correlated with `df_index` and 1 other fields	High correlation
`loan_amnt` is highly correlated with `installment` and 1 other fields	High correlation
`open_acc` is highly correlated with `total_acc`	High correlation
`revol_util` is highly correlated with `fico_range_high` and 1 other fields	High correlation
`sub_grade` is highly correlated with `fico_range_high` and 4 other fields	High correlation
`term` is highly correlated with `int_rate` and 2 other fields	High correlation
`total_acc` is highly correlated with `open_acc`	High correlation
`member_id` has 107843 (100.0%) missing values	Missing
`desc` has 68904 (63.9%) missing values	Missing
`emp_length` has 4806 (4.5%) missing values	Missing
`emp_title` has 6889 (6.4%) missing values	Missing
`annual_inc` is highly skewed (γ1 = 21.6135325)	Skewed
`pub_rec` is highly skewed (γ1 = 26.89434201)	Skewed
`revol_bal` is highly skewed (γ1 = 28.52620479)	Skewed
`df_index` is uniformly distributed	Uniform
`desc` is uniformly distributed	Uniform
`df_index` has unique values	Unique
`id` has unique values	Unique
`member_id` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`mort_acc` has 41241 (38.2%) zeros	Zeros
`pub_rec` has 94951 (88.0%) zeros	Zeros
`pub_rec_bankruptcies` has 96310 (89.3%) zeros	Zeros

Reproduction

Analysis started	2022-04-10 15:28:52.966449
Analysis finished	2022-04-10 15:30:14.679529
Duration	1 minute and 21.71 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

df_index
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIFORM
UNIQUE

Distinct	107843
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	67394.81161

Minimum	0
Maximum	134803
Zeros	1
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	842.6 KiB

Quantile statistics

Minimum	0
5-th percentile	6728.2
Q1	33738.5
median	67364
Q3	101130
95-th percentile	128060.9
Maximum	134803
Range	134803
Interquartile range (IQR)	67391.5

Descriptive statistics

Standard deviation	38907.88327
Coefficient of variation (CV)	0.5773127388
Kurtosis	-1.19872438
Mean	67394.81161
Median Absolute Deviation (MAD)	33699
Skewness	0.0003466812915
Sum	7268058668
Variance	1513823381
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
23251	1	< 0.1%
18730	1	< 0.1%
72594	1	< 0.1%
28246	1	< 0.1%
117499	1	< 0.1%
92032	1	< 0.1%
62000	1	< 0.1%
89447	1	< 0.1%
41896	1	< 0.1%
66680	1	< 0.1%
Other values (107833)	107833	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	1	< 0.1%
3	1	< 0.1%
4	1	< 0.1%
6	1	< 0.1%
7	1	< 0.1%
8	1	< 0.1%
9	1	< 0.1%
10	1	< 0.1%
11	1	< 0.1%

Value	Count	Frequency (%)
134803	1	< 0.1%
134802	1	< 0.1%
134801	1	< 0.1%
134800	1	< 0.1%
134799	1	< 0.1%
134798	1	< 0.1%
134797	1	< 0.1%
134796	1	< 0.1%
134795	1	< 0.1%
134794	1	< 0.1%

id
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct	107843
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6290486.691

Minimum	356706
Maximum	10234817
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	842.6 KiB

Quantile statistics

Minimum	356706
5-th percentile	3153397
Q1	4525573
median	6328585
Q3	7725772.5
95-th percentile	9744665.7
Maximum	10234817
Range	9878111
Interquartile range (IQR)	3200199.5

Descriptive statistics

Standard deviation	2073355.307
Coefficient of variation (CV)	0.3296017318
Kurtosis	-0.9953355535
Mean	6290486.691
Median Absolute Deviation (MAD)	1716133
Skewness	-0.01627983342
Sum	6.783849562 × 10¹¹
Variance	4.298802229 × 10¹²
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
8605612	1	< 0.1%
8545524	1	< 0.1%
5768833	1	< 0.1%
8575046	1	< 0.1%
3364910	1	< 0.1%
5435137	1	< 0.1%
6646516	1	< 0.1%
5606177	1	< 0.1%
7535684	1	< 0.1%
6564929	1	< 0.1%
Other values (107833)	107833	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
356706	1	< 0.1%
380041	1	< 0.1%
442319	1	< 0.1%
476326	1	< 0.1%
546966	1	< 0.1%
565935	1	< 0.1%
586040	1	< 0.1%
621950	1	< 0.1%
631299	1	< 0.1%
641849	1	< 0.1%

Value	Count	Frequency (%)
10234817	1	< 0.1%
10234814	1	< 0.1%
10234813	1	< 0.1%
10234796	1	< 0.1%
10234755	1	< 0.1%
10234750	1	< 0.1%
10234599	1	< 0.1%
10234574	1	< 0.1%
10224834	1	< 0.1%
10224828	1	< 0.1%

Charged off
Boolean

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	105.4 KiB

False	91024
True	16819

Common Values
Chart

Value	Count	Frequency (%)
False	91024	84.4%
True	16819	15.6%

member_id
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing	107843
Missing (%)	100.0%
Memory size	842.6 KiB

addr_state
Categorical

HIGH CORRELATION

Distinct	48
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	842.6 KiB

CA	17228
NY	8915
TX	8258
FL	7125
IL	4198
Other values (43)	62119

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	2 ?
Unique (%)	< 0.1%

Sample

1st row	WV
2nd row	NY
3rd row	CA
4th row	NC
5th row	TX

Common Values

Value	Count	Frequency (%)
CA	17228	16.0%
NY	8915	8.3%
TX	8258	7.7%
FL	7125	6.6%
IL	4198	3.9%
NJ	4083	3.8%
PA	3660	3.4%
OH	3446	3.2%
GA	3383	3.1%
VA	3274	3.0%
Other values (38)	44273	41.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
ca	17228	16.0%
ny	8915	8.3%
tx	8258	7.7%
fl	7125	6.6%
il	4198	3.9%
nj	4083	3.8%
pa	3660	3.4%
oh	3446	3.2%
ga	3383	3.1%
va	3274	3.0%
Other values (38)	44273	41.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

annual_inc
Real number (ℝ_≥0)

SKEWED

Distinct	10086
Distinct (%)	9.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	73218.32335

Minimum	6000
Maximum	6100000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	842.6 KiB

Quantile statistics

Minimum	6000
5-th percentile	30000
Q1	45750.06
median	63936
Q3	89000
95-th percentile	147810.3
Maximum	6100000
Range	6094000
Interquartile range (IQR)	43249.94

Descriptive statistics

Standard deviation	49583.80198
Coefficient of variation (CV)	0.6772048267
Kurtosis	2116.093894
Mean	73218.32335
Median Absolute Deviation (MAD)	20064
Skewness	21.6135325
Sum	7896083645
Variance	2458553419
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
60000	4146	3.8%
50000	3862	3.6%
65000	3138	2.9%
40000	2965	2.7%
70000	2960	2.7%
80000	2868	2.7%
45000	2792	2.6%
75000	2711	2.5%
55000	2698	2.5%
100000	2051	1.9%
Other values (10076)	77652	72.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
6000	1	< 0.1%
7200	1	< 0.1%
7500	1	< 0.1%
8000	2	< 0.1%
8200	1	< 0.1%
8400	1	< 0.1%
8412	1	< 0.1%
8500	2	< 0.1%
8520	3	< 0.1%
8664	1	< 0.1%

Value	Count	Frequency (%)
6100000	1	< 0.1%
2000000	2	< 0.1%
1510000	1	< 0.1%
1350000	1	< 0.1%
1300000	1	< 0.1%
1250000	1	< 0.1%
1200000	2	< 0.1%
1050000	1	< 0.1%
1000000	4	< 0.1%
990000	1	< 0.1%

application_type
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	842.6 KiB

Individual	107843

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Individual
2nd row	Individual
3rd row	Individual
4th row	Individual
5th row	Individual

Common Values

Value	Count	Frequency (%)
Individual	107843	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
individual	107843	100.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

desc
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct	38454
Distinct (%)	98.8%
Missing	68904
Missing (%)	63.9%
Memory size	842.6 KiB

Borrower added on 07/25/13 > Debt consolidation<br>	6
Borrower added on 09/30/13 > Debt Consolidation<br>	5
Borrower added on 09/19/13 > Debt consolidation<br>	5
Borrower added on 01/14/13 > Debt consolidation<br>	5
Borrower added on 12/16/13 > Debt consolidation<br>	4
Other values (38449)	38914

Length

Max length	2365
Median length	134
Mean length	166.8376435
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	38105 ?
Unique (%)	97.9%

Sample

1st row	Borrower added on 11/05/13 > I need to get a new roof on my house and pay the remainder money on credit cards.<br>
2nd row	Borrower added on 12/17/13 > We would like to put in hardwood floors and paint the exterior of the house.<br>
3rd row	Borrower added on 01/29/13 > New refrigerator and oven.<br>
4th row	Borrower added on 09/09/13 > I need to pay some credit cards off and there a purchase I want to make.<br>
5th row	Borrower added on 02/06/13 > I am really tired of being in credit card debt and I want to purchase my first house. By consolidating and paying off all of my debt (other than my car), I can buy a home and not have to worry about credit card debt anymore.<br>

Common Values

Value	Count	Frequency (%)
Borrower added on 07/25/13 > Debt consolidation<br>	6	< 0.1%
Borrower added on 09/30/13 > Debt Consolidation<br>	5	< 0.1%
Borrower added on 09/19/13 > Debt consolidation<br>	5	< 0.1%
Borrower added on 01/14/13 > Debt consolidation<br>	5	< 0.1%
Borrower added on 12/16/13 > Debt consolidation<br>	4	< 0.1%
Borrower added on 12/19/13 > Debt consolidation<br>	4	< 0.1%
Borrower added on 11/05/13 > Debt Consolidation<br>	4	< 0.1%
Borrower added on 10/09/13 > Debt consolidation<br>	4	< 0.1%
Borrower added on 02/27/13 > Debt consolidation<br>	4	< 0.1%
Borrower added on 12/10/13 > Debt consolidation<br>	4	< 0.1%
Other values (38444)	38894	36.1%
(Missing)	68904	63.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
on	51143	4.4%
to	48696	4.2%
	45038	3.9%
borrower	43999	3.8%
added	43819	3.8%
i	34124	3.0%
and	29148	2.5%
credit	27868	2.4%
my	27797	2.4%
a	22273	1.9%
Other values (22445)	776840	67.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

dti
Real number (ℝ_≥0)

Distinct	3492
Distinct (%)	3.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	17.21222935

Minimum	0
Maximum	34.99
Zeros	37
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	842.6 KiB

Quantile statistics

Minimum	0
5-th percentile	5.2
Q1	11.47
median	16.89
Q3	22.78
95-th percentile	30.17
Maximum	34.99
Range	34.99
Interquartile range (IQR)	11.31

Descriptive statistics

Standard deviation	7.595111355
Coefficient of variation (CV)	0.4412625
Kurtosis	-0.683981209
Mean	17.21222935
Median Absolute Deviation (MAD)	5.64
Skewness	0.1324209301
Sum	1856218.45
Variance	57.68571649
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
14.4	125	0.1%
18	92	0.1%
15.6	88	0.1%
12	82	0.1%
19.2	80	0.1%
16.8	80	0.1%
12.72	79	0.1%
12.48	78	0.1%
9.6	77	0.1%
16.32	77	0.1%
Other values (3482)	106985	99.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	37	< 0.1%
0.01	2	< 0.1%
0.02	1	< 0.1%
0.03	1	< 0.1%
0.06	2	< 0.1%
0.07	2	< 0.1%
0.08	2	< 0.1%
0.11	1	< 0.1%
0.12	1	< 0.1%
0.13	1	< 0.1%

Value	Count	Frequency (%)
34.99	5	< 0.1%
34.98	6	< 0.1%
34.97	8	< 0.1%
34.96	8	< 0.1%
34.95	10	< 0.1%
34.94	4	< 0.1%
34.93	10	< 0.1%
34.92	6	< 0.1%
34.91	3	< 0.1%
34.9	7	< 0.1%

earliest_cr_line
Categorical

HIGH CARDINALITY

Distinct	601
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	842.6 KiB

Oct-2000	913
Oct-2001	846
Oct-1999	842
Dec-2000	841
Nov-1999	827
Other values (596)	103574

Length

Max length	8
Median length	8
Mean length	8
Min length	8

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	44 ?
Unique (%)	< 0.1%

Sample

1st row	Oct-2001
2nd row	Aug-1998
3rd row	Feb-2000
4th row	Jun-2000
5th row	Mar-1982

Common Values

Value	Count	Frequency (%)
Oct-2000	913	0.8%
Oct-2001	846	0.8%
Oct-1999	842	0.8%
Dec-2000	841	0.8%
Nov-1999	827	0.8%
Nov-2000	814	0.8%
Dec-1999	766	0.7%
Dec-2001	761	0.7%
Jan-2001	761	0.7%
Aug-2000	760	0.7%
Other values (591)	99712	92.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
oct-2000	913	0.8%
oct-2001	846	0.8%
oct-1999	842	0.8%
dec-2000	841	0.8%
nov-1999	827	0.8%
nov-2000	814	0.8%
dec-1999	766	0.7%
dec-2001	761	0.7%
jan-2001	761	0.7%
aug-2000	760	0.7%
Other values (591)	99712	92.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

emp_length
Categorical

HIGH CORRELATION
MISSING

Distinct	11
Distinct (%)	< 0.1%
Missing	4806
Missing (%)	4.5%
Memory size	842.6 KiB

10+ years	36566
2 years	9039
3 years	8089
5 years	7779
< 1 year	7260
Other values (6)	34304

Length

Max length	9
Median length	7
Mean length	7.72025583
Min length	6

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1 year
2nd row	10+ years
3rd row	5 years
4th row	10+ years
5th row	10+ years

Common Values

Value	Count	Frequency (%)
10+ years	36566	33.9%
2 years	9039	8.4%
3 years	8089	7.5%
5 years	7779	7.2%
< 1 year	7260	6.7%
6 years	6529	6.1%
7 years	6520	6.0%
1 year	6179	5.7%
4 years	5496	5.1%
8 years	5388	5.0%
(Missing)	4806	4.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
years	89598	42.0%
10	36566	17.1%
1	13439	6.3%
year	13439	6.3%
2	9039	4.2%
3	8089	3.8%
5	7779	3.6%
	7260	3.4%
6	6529	3.1%
7	6520	3.1%
Other values (3)	15076	7.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

emp_title
Categorical

HIGH CARDINALITY
MISSING

Distinct	68454
Distinct (%)	67.8%
Missing	6889
Missing (%)	6.4%
Memory size	842.6 KiB

Teacher	681
Manager	544
RN	311
Registered Nurse	281
US Army	249
Other values (68449)	98888

Length

Max length	42
Median length	17
Mean length	17.59528102
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	60694 ?
Unique (%)	60.1%

Sample

1st row	Dollar General
2nd row	City and County of San Francisco
3rd row	TREASURER
4th row	GENERAL MANAGER
5th row	Foreman

Common Values

Value	Count	Frequency (%)
Teacher	681	0.6%
Manager	544	0.5%
RN	311	0.3%
Registered Nurse	281	0.3%
US Army	249	0.2%
Supervisor	247	0.2%
Project Manager	202	0.2%
Sales	176	0.2%
Office Manager	174	0.2%
Bank of America	172	0.2%
Other values (68444)	97917	90.8%
(Missing)	6889	6.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
of	6387	2.5%
manager	5392	2.1%
inc	5160	2.0%
	2683	1.1%
center	2015	0.8%
county	1912	0.8%
services	1725	0.7%
medical	1711	0.7%
school	1709	0.7%
hospital	1665	0.7%
Other values (31752)	221851	88.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

fico_range_high
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	38
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	699.0001205

Minimum	664
Maximum	850
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	842.6 KiB

Quantile statistics

Minimum	664
5-th percentile	664
Q1	679
median	694
Q3	714
95-th percentile	754
Maximum	850
Range	186
Interquartile range (IQR)	35

Descriptive statistics

Standard deviation	28.74380345
Coefficient of variation (CV)	0.04112131401
Kurtosis	2.437018684
Mean	699.0001205
Median Absolute Deviation (MAD)	15
Skewness	1.369327412
Sum	75382270
Variance	826.2062369
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=38)

Value	Count	Frequency (%)
674	9100	8.4%
684	9011	8.4%
679	8416	7.8%
669	8389	7.8%
694	8275	7.7%
689	8239	7.6%
664	7716	7.2%
699	7486	6.9%
704	6731	6.2%
709	6095	5.7%
Other values (28)	28385	26.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
664	7716	7.2%
669	8389	7.8%
674	9100	8.4%
679	8416	7.8%
684	9011	8.4%
689	8239	7.6%
694	8275	7.7%
699	7486	6.9%
704	6731	6.2%
709	6095	5.7%

Value	Count	Frequency (%)
850	8	< 0.1%
844	15	< 0.1%
839	24	< 0.1%
834	40	< 0.1%
829	69	0.1%
824	97	0.1%
819	126	0.1%
814	135	0.1%
809	189	0.2%
804	200	0.2%

fico_range_low
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	38
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	695.0000464

Minimum	660
Maximum	845
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	842.6 KiB

Quantile statistics

Minimum	660
5-th percentile	660
Q1	675
median	690
Q3	710
95-th percentile	750
Maximum	845
Range	185
Interquartile range (IQR)	35

Descriptive statistics

Standard deviation	28.74341504
Coefficient of variation (CV)	0.04135742895
Kurtosis	2.435844723
Mean	695.0000464
Median Absolute Deviation (MAD)	15
Skewness	1.369178396
Sum	74950890
Variance	826.1839079
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=38)

Value	Count	Frequency (%)
670	9100	8.4%
680	9011	8.4%
675	8416	7.8%
665	8389	7.8%
690	8275	7.7%
685	8239	7.6%
660	7716	7.2%
695	7486	6.9%
700	6731	6.2%
705	6095	5.7%
Other values (28)	28385	26.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
660	7716	7.2%
665	8389	7.8%
670	9100	8.4%
675	8416	7.8%
680	9011	8.4%
685	8239	7.6%
690	8275	7.7%
695	7486	6.9%
700	6731	6.2%
705	6095	5.7%

Value	Count	Frequency (%)
845	8	< 0.1%
840	15	< 0.1%
835	24	< 0.1%
830	40	< 0.1%
825	69	0.1%
820	97	0.1%
815	126	0.1%
810	135	0.1%
805	189	0.2%
800	200	0.2%

grade
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	7
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	842.6 KiB

B	35307
C	30395
D	16517
A	14183
E	7216
Other values (2)	4225

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	C
2nd row	C
3rd row	D
4th row	C
5th row	A

Common Values

Value	Count	Frequency (%)
B	35307	32.7%
C	30395	28.2%
D	16517	15.3%
A	14183	13.2%
E	7216	6.7%
F	3515	3.3%
G	710	0.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
b	35307	32.7%
c	30395	28.2%
d	16517	15.3%
a	14183	13.2%
e	7216	6.7%
f	3515	3.3%
g	710	0.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

home_ownership
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	842.6 KiB

MORTGAGE	57648
RENT	41171
OWN	9024

Length

Max length	8
Median length	8
Mean length	6.054542251
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	MORTGAGE
2nd row	RENT
3rd row	RENT
4th row	OWN
5th row	OWN

Common Values

Value	Count	Frequency (%)
MORTGAGE	57648	53.5%
RENT	41171	38.2%
OWN	9024	8.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
mortgage	57648	53.5%
rent	41171	38.2%
own	9024	8.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

initial_list_status
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	842.6 KiB

f	79060
w	28783

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	w
2nd row	w
3rd row	w
4th row	f
5th row	w

Common Values

Value	Count	Frequency (%)
f	79060	73.3%
w	28783	26.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
f	79060	73.3%
w	28783	26.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

installment
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	21823
Distinct (%)	20.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	452.7542992

Minimum	23.26
Maximum	1408.13
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	842.6 KiB

Quantile statistics

Minimum	23.26
5-th percentile	132.75
Q1	280.95
median	404.97
Q3	587.73
95-th percentile	921.85
Maximum	1408.13
Range	1384.87
Interquartile range (IQR)	306.78

Descriptive statistics

Standard deviation	240.9649629
Coefficient of variation (CV)	0.5322201542
Kurtosis	0.7452291431
Mean	452.7542992
Median Absolute Deviation (MAD)	146.23
Skewness	0.9000082203
Sum	48826381.89
Variance	58064.11336
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
337.47	318	0.3%
635.07	298	0.3%
317.54	296	0.3%
332.72	292	0.3%
332.1	280	0.3%
328.06	278	0.3%
343.39	277	0.3%
476.3	255	0.2%
625.81	246	0.2%
327.34	239	0.2%
Other values (21813)	105064	97.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
23.26	1	< 0.1%
25.86	1	< 0.1%
28.82	1	< 0.1%
29.52	1	< 0.1%
29.83	1	< 0.1%
30.71	1	< 0.1%
31.3	1	< 0.1%
31.62	1	< 0.1%
31.76	2	< 0.1%
32	1	< 0.1%

Value	Count	Frequency (%)
1408.13	1	< 0.1%
1407.01	1	< 0.1%
1406.45	4	< 0.1%
1396.79	1	< 0.1%
1391.41	2	< 0.1%
1388.45	1	< 0.1%
1382.36	2	< 0.1%
1374.63	4	< 0.1%
1368.75	1	< 0.1%
1367.65	3	< 0.1%

int_rate
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	100
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	14.53027568

Minimum	6
Maximum	26.06
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	842.6 KiB

Quantile statistics

Minimum	6
5-th percentile	7.62
Q1	11.14
median	14.33
Q3	17.56
95-th percentile	22.47
Maximum	26.06
Range	20.06
Interquartile range (IQR)	6.42

Descriptive statistics

Standard deviation	4.439836193
Coefficient of variation (CV)	0.305557602
Kurtosis	-0.4741654952
Mean	14.53027568
Median Absolute Deviation (MAD)	3.19
Skewness	0.2433553994
Sum	1566988.52
Variance	19.71214542
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
8.9	4039	3.7%
14.33	3880	3.6%
13.11	3721	3.5%
12.12	3544	3.3%
11.14	3397	3.1%
7.9	2775	2.6%
15.8	2745	2.5%
11.99	2704	2.5%
10.99	2554	2.4%
16.29	2546	2.4%
Other values (90)	75938	70.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
6	21	< 0.1%
6.03	2032	1.9%
6.62	1720	1.6%
6.97	322	0.3%
7.62	2524	2.3%
7.9	2775	2.6%
8.6	333	0.3%
8.9	4039	3.7%
9.25	437	0.4%
9.67	1291	1.2%

Value	Count	Frequency (%)
26.06	44	< 0.1%
25.99	48	< 0.1%
25.89	95	0.1%
25.83	119	0.1%
25.8	161	0.1%
25.57	125	0.1%
25.28	134	0.1%
24.99	187	0.2%
24.89	239	0.2%
24.83	58	0.1%

issue_d
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	12
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	842.6 KiB

Dec-2013	12019
Nov-2013	11760
Oct-2013	11281
Sep-2013	10434
Aug-2013	10173
Other values (7)	52176

Length

Max length	8
Median length	8
Mean length	8
Min length	8

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Nov-2013
2nd row	Apr-2013
3rd row	Sep-2013
4th row	Dec-2013
5th row	Dec-2013

Common Values

Value	Count	Frequency (%)
Dec-2013	12019	11.1%
Nov-2013	11760	10.9%
Oct-2013	11281	10.5%
Sep-2013	10434	9.7%
Aug-2013	10173	9.4%
Jul-2013	9538	8.8%
Jun-2013	8697	8.1%
May-2013	8210	7.6%
Apr-2013	7564	7.0%
Mar-2013	6649	6.2%
Other values (2)	11518	10.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
dec-2013	12019	11.1%
nov-2013	11760	10.9%
oct-2013	11281	10.5%
sep-2013	10434	9.7%
aug-2013	10173	9.4%
jul-2013	9538	8.8%
jun-2013	8697	8.1%
may-2013	8210	7.6%
apr-2013	7564	7.0%
mar-2013	6649	6.2%
Other values (2)	11518	10.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

loan_amnt
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	1191
Distinct (%)	1.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	14719.79336

Minimum	1000
Maximum	35000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	842.6 KiB

Quantile statistics

Minimum	1000
5-th percentile	4000
Q1	8500
median	13100
Q3	20000
95-th percentile	30000
Maximum	35000
Range	34000
Interquartile range (IQR)	11500

Descriptive statistics

Standard deviation	8106.966678
Coefficient of variation (CV)	0.5507527505
Kurtosis	-0.2023106382
Mean	14719.79336
Median Absolute Deviation (MAD)	5350
Skewness	0.6605167458
Sum	1587426675
Variance	65722908.71
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
10000	7885	7.3%
12000	5773	5.4%
15000	5626	5.2%
20000	5570	5.2%
8000	3527	3.3%
35000	3467	3.2%
16000	3211	3.0%
18000	2966	2.8%
24000	2803	2.6%
6000	2684	2.5%
Other values (1181)	64331	59.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1000	278	0.3%
1025	1	< 0.1%
1100	5	< 0.1%
1125	3	< 0.1%
1150	5	< 0.1%
1175	1	< 0.1%
1200	167	0.2%
1225	1	< 0.1%
1250	7	< 0.1%
1275	3	< 0.1%

Value	Count	Frequency (%)
35000	3467	3.2%
34975	5	< 0.1%
34900	1	< 0.1%
34800	9	< 0.1%
34750	1	< 0.1%
34700	1	< 0.1%
34575	1	< 0.1%
34500	11	< 0.1%
34475	70	0.1%
34400	2	< 0.1%

mort_acc
Real number (ℝ_≥0)

ZEROS

Distinct	25
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.879361665

Minimum	0
Maximum	31
Zeros	41241
Zeros (%)	38.2%
Negative	0
Negative (%)	0.0%
Memory size	842.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	3
95-th percentile	6
Maximum	31
Range	31
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	2.193544261
Coefficient of variation (CV)	1.167175165
Kurtosis	3.357413832
Mean	1.879361665
Median Absolute Deviation (MAD)	1
Skewness	1.484571965
Sum	202676
Variance	4.811636424
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=25)

Value	Count	Frequency (%)
0	41241	38.2%
1	18112	16.8%
2	14648	13.6%
3	11397	10.6%
4	8702	8.1%
5	5826	5.4%
6	3509	3.3%
7	2051	1.9%
8	1090	1.0%
9	615	0.6%
Other values (15)	652	0.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	41241	38.2%
1	18112	16.8%
2	14648	13.6%
3	11397	10.6%
4	8702	8.1%
5	5826	5.4%
6	3509	3.3%
7	2051	1.9%
8	1090	1.0%
9	615	0.6%

Value	Count	Frequency (%)
31	1	< 0.1%
30	1	< 0.1%
27	1	< 0.1%
24	3	< 0.1%
20	3	< 0.1%
19	3	< 0.1%
18	3	< 0.1%
17	5	< 0.1%
16	12	< 0.1%
15	17	< 0.1%

open_acc
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	54
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	11.15074692

Minimum	0
Maximum	62
Zeros	3
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	842.6 KiB

Quantile statistics

Minimum	0
5-th percentile	5
Q1	8
median	10
Q3	14
95-th percentile	20
Maximum	62
Range	62
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	4.653656505
Coefficient of variation (CV)	0.4173403395
Kurtosis	2.086879721
Mean	11.15074692
Median Absolute Deviation (MAD)	3
Skewness	1.016487942
Sum	1202530
Variance	21.65651886
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
9	10701	9.9%
10	10324	9.6%
8	9968	9.2%
11	9538	8.8%
7	8731	8.1%
12	8343	7.7%
13	6996	6.5%
6	6808	6.3%
14	6035	5.6%
15	4842	4.5%
Other values (44)	25557	23.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	3	< 0.1%
1	31	< 0.1%
2	278	0.3%
3	913	0.8%
4	2352	2.2%
5	4601	4.3%
6	6808	6.3%
7	8731	8.1%
8	9968	9.2%
9	10701	9.9%

Value	Count	Frequency (%)
62	1	< 0.1%
53	2	< 0.1%
52	1	< 0.1%
51	1	< 0.1%
50	1	< 0.1%
49	2	< 0.1%
48	1	< 0.1%
46	1	< 0.1%
45	2	< 0.1%
44	1	< 0.1%

pub_rec
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED
ZEROS

Distinct	14
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.1381638122

Minimum	0
Maximum	54
Zeros	94951
Zeros (%)	88.0%
Negative	0
Negative (%)	0.0%
Memory size	842.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	1
Maximum	54
Range	54
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.4767294832
Coefficient of variation (CV)	3.450465615
Kurtosis	2564.487209
Mean	0.1381638122
Median Absolute Deviation (MAD)	0
Skewness	26.89434201
Sum	14900
Variance	0.2272710001
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=14)

Value	Count	Frequency (%)
0	94951	88.0%
1	11665	10.8%
2	861	0.8%
3	209	0.2%
4	75	0.1%
5	37	< 0.1%
6	21	< 0.1%
7	13	< 0.1%
8	5	< 0.1%
11	2	< 0.1%
Other values (4)	4	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	94951	88.0%
1	11665	10.8%
2	861	0.8%
3	209	0.2%
4	75	0.1%
5	37	< 0.1%
6	21	< 0.1%
7	13	< 0.1%
8	5	< 0.1%
9	1	< 0.1%

Value	Count	Frequency (%)
54	1	< 0.1%
49	1	< 0.1%
11	2	< 0.1%
10	1	< 0.1%
9	1	< 0.1%
8	5	< 0.1%
7	13	< 0.1%
6	21	< 0.1%
5	37	< 0.1%
4	75	0.1%

pub_rec_bankruptcies
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	9
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.1099746854

Minimum	0
Maximum	8
Zeros	96310
Zeros (%)	89.3%
Negative	0
Negative (%)	0.0%
Memory size	842.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	1
Maximum	8
Range	8
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.3262656157
Coefficient of variation (CV)	2.966733793
Kurtosis	16.70140439
Mean	0.1099746854
Median Absolute Deviation (MAD)	0
Skewness	3.222420361
Sum	11860
Variance	0.106449252
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
0	96310	89.3%
1	11287	10.5%
2	196	0.2%
3	31	< 0.1%
4	14	< 0.1%
6	2	< 0.1%
8	1	< 0.1%
5	1	< 0.1%
7	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	96310	89.3%
1	11287	10.5%
2	196	0.2%
3	31	< 0.1%
4	14	< 0.1%
5	1	< 0.1%
6	2	< 0.1%
7	1	< 0.1%
8	1	< 0.1%

Value	Count	Frequency (%)
8	1	< 0.1%
7	1	< 0.1%
6	2	< 0.1%
5	1	< 0.1%
4	14	< 0.1%
3	31	< 0.1%
2	196	0.2%
1	11287	10.5%
0	96310	89.3%

purpose
Categorical

HIGH CORRELATION

Distinct	13
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	842.6 KiB

debt_consolidation	64530
credit_card	26243
home_improvement	5926
other	4647
major_purchase	1812
Other values (8)	4685

Length

Max length	18
Median length	18
Mean length	15.11400833
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	debt_consolidation
2nd row	credit_card
3rd row	other
4th row	home_improvement
5th row	debt_consolidation

Common Values

Value	Count	Frequency (%)
debt_consolidation	64530	59.8%
credit_card	26243	24.3%
home_improvement	5926	5.5%
other	4647	4.3%
major_purchase	1812	1.7%
small_business	1087	1.0%
car	829	0.8%
medical	722	0.7%
house	557	0.5%
moving	502	0.5%
Other values (3)	988	0.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
debt_consolidation	64530	59.8%
credit_card	26243	24.3%
home_improvement	5926	5.5%
other	4647	4.3%
major_purchase	1812	1.7%
small_business	1087	1.0%
car	829	0.8%
medical	722	0.7%
house	557	0.5%
moving	502	0.5%
Other values (3)	988	0.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

revol_bal
Real number (ℝ_≥0)

HIGH CORRELATION
SKEWED

Distinct	37020
Distinct (%)	34.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	16812.6326

Minimum	0
Maximum	2568995
Zeros	273
Zeros (%)	0.3%
Negative	0
Negative (%)	0.0%
Memory size	842.6 KiB

Quantile statistics

Minimum	0
5-th percentile	2976.1
Q1	7334
median	12705
Q3	21112.5
95-th percentile	38945.7
Maximum	2568995
Range	2568995
Interquartile range (IQR)	13778.5

Descriptive statistics

Standard deviation	20758.36014
Coefficient of variation (CV)	1.234688262
Kurtosis	2655.224282
Mean	16812.6326
Median Absolute Deviation (MAD)	6303
Skewness	28.52620479
Sum	1813124738
Variance	430909515.6
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	273	0.3%
7429	16	< 0.1%
6852	15	< 0.1%
9529	15	< 0.1%
11874	14	< 0.1%
5896	14	< 0.1%
8979	14	< 0.1%
8881	14	< 0.1%
11363	14	< 0.1%
9334	13	< 0.1%
Other values (37010)	107441	99.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	273	0.3%
1	4	< 0.1%
2	6	< 0.1%
3	6	< 0.1%
4	7	< 0.1%
5	2	< 0.1%
6	2	< 0.1%
7	4	< 0.1%
8	2	< 0.1%
9	4	< 0.1%

Value	Count	Frequency (%)
2568995	1	< 0.1%
1746716	1	< 0.1%
694615	1	< 0.1%
617838	1	< 0.1%
605627	1	< 0.1%
570842	1	< 0.1%
509875	1	< 0.1%
491712	1	< 0.1%
488421	1	< 0.1%
481912	1	< 0.1%

revol_util
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	1062
Distinct (%)	1.0%
Missing	59
Missing (%)	0.1%
Infinite	0
Infinite (%)	0.0%
Mean	58.58248349

Minimum	0
Maximum	128.1
Zeros	290
Zeros (%)	0.3%
Negative	0
Negative (%)	0.0%
Memory size	842.6 KiB

Quantile statistics

Minimum	0
5-th percentile	18.3
Q1	42.9
median	60.3
Q3	76.3
95-th percentile	92.2
Maximum	128.1
Range	128.1
Interquartile range (IQR)	33.4

Descriptive statistics

Standard deviation	22.5044375
Coefficient of variation (CV)	0.3841495984
Kurtosis	-0.5398613939
Mean	58.58248349
Median Absolute Deviation (MAD)	16.6
Skewness	-0.3468060351
Sum	6314254.4
Variance	506.4497074
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	290	0.3%
61.6	209	0.2%
67.4	204	0.2%
64.6	204	0.2%
67.9	203	0.2%
65.2	203	0.2%
72	200	0.2%
59.3	200	0.2%
56.4	200	0.2%
70.8	199	0.2%
Other values (1052)	105672	98.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	290	0.3%
0.1	35	< 0.1%
0.2	31	< 0.1%
0.3	24	< 0.1%
0.4	24	< 0.1%
0.5	14	< 0.1%
0.6	18	< 0.1%
0.7	24	< 0.1%
0.8	31	< 0.1%
0.9	22	< 0.1%

Value	Count	Frequency (%)
128.1	1	< 0.1%
127.6	1	< 0.1%
122.5	1	< 0.1%
120.2	2	< 0.1%
119.2	1	< 0.1%
115.3	1	< 0.1%
113.9	1	< 0.1%
112.7	1	< 0.1%
109.9	2	< 0.1%
109.3	1	< 0.1%

sub_grade
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	35
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	842.6 KiB

B4	8466
B3	8231
B2	7849
C3	6494
B1	6261
Other values (30)	70542

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	C2
2nd row	C3
3rd row	D2
4th row	C4
5th row	A4

Common Values

Value	Count	Frequency (%)
B4	8466	7.9%
B3	8231	7.6%
B2	7849	7.3%
C3	6494	6.0%
B1	6261	5.8%
C4	6233	5.8%
C1	6103	5.7%
C2	5848	5.4%
C5	5717	5.3%
D1	4502	4.2%
Other values (25)	42139	39.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
b4	8466	7.9%
b3	8231	7.6%
b2	7849	7.3%
c3	6494	6.0%
b1	6261	5.8%
c4	6233	5.8%
c1	6103	5.7%
c2	5848	5.4%
c5	5717	5.3%
d1	4502	4.2%
Other values (25)	42139	39.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

term
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	842.6 KiB

36 months	80314
60 months	27529

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	60 months
2nd row	36 months
3rd row	36 months
4th row	60 months
5th row	36 months

Common Values

Value	Count	Frequency (%)
36 months	80314	74.5%
60 months	27529	25.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
months	107843	50.0%
36	80314	37.2%
60	27529	12.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

title
Categorical

HIGH CARDINALITY

Distinct	26875
Distinct (%)	24.9%
Missing	4
Missing (%)	< 0.1%
Memory size	842.6 KiB

Debt consolidation	14837
Debt Consolidation	7170
Credit card refinancing	5333
Consolidation	2851
debt consolidation	2324
Other values (26870)	75324

Length

Max length	40
Median length	18
Mean length	16.16851974
Min length	2

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	22437 ?
Unique (%)	20.8%

Sample

1st row	Money
2nd row	My Loan
3rd row	Other
4th row	HOME IMPROVEMENT LOAN
5th row	Chase-AMEX payoff

Common Values

Value	Count	Frequency (%)
Debt consolidation	14837	13.8%
Debt Consolidation	7170	6.6%
Credit card refinancing	5333	4.9%
Consolidation	2851	2.6%
debt consolidation	2324	2.2%
Other	1467	1.4%
Home improvement	1230	1.1%
consolidation	1136	1.1%
Credit Card Consolidation	1089	1.0%
Debt Consolidation Loan	863	0.8%
Other values (26865)	69539	64.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
consolidation	38682	15.8%
debt	37942	15.5%
credit	19565	8.0%
card	15675	6.4%
loan	13284	5.4%
refinancing	5761	2.4%
home	4866	2.0%
payoff	4550	1.9%
pay	3857	1.6%
off	3316	1.4%
Other values (7812)	97315	39.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

total_acc
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	81
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	24.90932188

Minimum	2
Maximum	105
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	842.6 KiB

Quantile statistics

Minimum	2
5-th percentile	10
Q1	17
median	23
Q3	31
95-th percentile	46
Maximum	105
Range	103
Interquartile range (IQR)	14

Descriptive statistics

Standard deviation	11.10443396
Coefficient of variation (CV)	0.4457943101
Kurtosis	0.5507030228
Mean	24.90932188
Median Absolute Deviation (MAD)	7
Skewness	0.7596197399
Sum	2686296
Variance	123.3084537
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
22	4113	3.8%
20	4071	3.8%
21	4058	3.8%
23	4050	3.8%
17	4045	3.8%
18	4003	3.7%
19	3975	3.7%
24	3951	3.7%
25	3709	3.4%
26	3684	3.4%
Other values (71)	68184	63.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
2	7	< 0.1%
3	68	0.1%
4	212	0.2%
5	377	0.3%
6	663	0.6%
7	984	0.9%
8	1307	1.2%
9	1623	1.5%
10	2064	1.9%
11	2337	2.2%

Value	Count	Frequency (%)
105	1	< 0.1%
98	1	< 0.1%
88	1	< 0.1%
84	1	< 0.1%
83	1	< 0.1%
82	1	< 0.1%
80	2	< 0.1%
79	2	< 0.1%
78	1	< 0.1%
75	1	< 0.1%

verification_status
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	842.6 KiB

Verified	52968
Not Verified	31107
Source Verified	23768

Length

Max length	15
Median length	12
Mean length	10.69654961
Min length	8

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Verified
2nd row	Not Verified
3rd row	Not Verified
4th row	Verified
5th row	Source Verified

Common Values

Value	Count	Frequency (%)
Verified	52968	49.1%
Not Verified	31107	28.8%
Source Verified	23768	22.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
verified	107843	66.3%
not	31107	19.1%
source	23768	14.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

zip_code
Categorical

HIGH CARDINALITY

Distinct	828
Distinct (%)	0.8%
Missing	0
Missing (%)	0.0%
Memory size	842.6 KiB

945xx	1306
750xx	1161
112xx	1124
606xx	1054
900xx	964
Other values (823)	102234

Length

Max length	5
Median length	5
Mean length	5
Min length	5

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	15 ?
Unique (%)	< 0.1%

Sample

1st row	254xx
2nd row	136xx
3rd row	941xx
4th row	277xx
5th row	757xx

Common Values

Value	Count	Frequency (%)
945xx	1306	1.2%
750xx	1161	1.1%
112xx	1124	1.0%
606xx	1054	1.0%
900xx	964	0.9%
100xx	933	0.9%
331xx	926	0.9%
300xx	910	0.8%
070xx	908	0.8%
917xx	863	0.8%
Other values (818)	97694	90.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
945xx	1306	1.2%
750xx	1161	1.1%
112xx	1124	1.0%
606xx	1054	1.0%
900xx	964	0.9%
100xx	933	0.9%
331xx	926	0.9%
300xx	910	0.8%
070xx	908	0.8%
917xx	863	0.8%
Other values (818)	97694	90.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	df_index	id	Charged off	member_id	addr_state	annual_inc	application_type	desc	dti	earliest_cr_line	emp_length	emp_title	fico_range_high	fico_range_low	grade	home_ownership	initial_list_status	installment	int_rate	issue_d	loan_amnt	mort_acc	open_acc	pub_rec	pub_rec_bankruptcies	purpose	revol_bal	revol_util	sub_grade	term	title	total_acc	verification_status	zip_code
0	23251	8605612	True	NaN	WV	45000.0	Individual	Borrower added on 11/05/13 > I need to get a new roof on my house and pay the remainder money on credit cards.<br>	19.63	Oct-2001	NaN	NaN	699.0	695.0	C	MORTGAGE	w	262.27	15.10	Nov-2013	11000.0	5.0	10.0	1.0	1.0	debt_consolidation	10270.0	54.3	C2	60 months	Money	27.0	Verified	254xx
1	108933	4174682	False	NaN	NY	26000.0	Individual	NaN	14.72	Aug-1998	1 year	Dollar General	689.0	685.0	C	RENT	w	291.87	15.80	Apr-2013	8325.0	2.0	10.0	0.0	0.0	credit_card	9528.0	63.1	C3	36 months	My Loan	19.0	Not Verified	136xx
2	55850	6896193	False	NaN	CA	72000.0	Individual	NaN	20.70	Feb-2000	10+ years	City and County of San Francisco	674.0	670.0	D	RENT	w	145.12	18.25	Sep-2013	4000.0	0.0	12.0	0.0	0.0	other	14687.0	71.0	D2	36 months	Other	14.0	Not Verified	941xx
3	4475	9827905	False	NaN	NC	32000.0	Individual	Borrower added on 12/17/13 > We would like to put in hardwood floors and paint the exterior of the house.<br>	19.63	Jun-2000	5 years	TREASURER	714.0	710.0	C	OWN	f	241.12	15.61	Dec-2013	10000.0	3.0	21.0	0.0	0.0	home_improvement	19773.0	30.1	C4	60 months	HOME IMPROVEMENT LOAN	40.0	Verified	277xx
4	11025	8978826	False	NaN	TX	85000.0	Individual	NaN	24.64	Mar-1982	10+ years	GENERAL MANAGER	739.0	735.0	A	OWN	w	876.13	7.90	Dec-2013	28000.0	1.0	9.0	0.0	0.0	debt_consolidation	22484.0	36.7	A4	36 months	Chase-AMEX payoff	20.0	Source Verified	757xx
5	30886	8244741	False	NaN	CT	52500.0	Individual	NaN	4.09	Dec-2006	10+ years	Foreman	669.0	665.0	B	MORTGAGE	f	204.67	12.99	Oct-2013	6075.0	2.0	8.0	0.0	0.0	credit_card	3011.0	49.4	B4	36 months	home improvment	12.0	Not Verified	065xx
6	127073	3235259	False	NaN	GA	120000.0	Individual	NaN	10.88	Apr-2003	< 1 year	ASVK TECHNOLOGIES	734.0	730.0	B	RENT	w	539.96	13.11	Feb-2013	16000.0	0.0	7.0	0.0	0.0	small_business	27823.0	60.7	B4	36 months	Business	16.0	Source Verified	300xx
7	111063	3811042	True	NaN	AL	30000.0	Individual	NaN	28.20	Dec-1998	< 1 year	Mandoki Hospitality Inc	694.0	690.0	C	RENT	f	171.70	14.33	Apr-2013	5000.0	0.0	11.0	0.0	0.0	credit_card	17299.0	49.1	C1	36 months	credit card payoff	15.0	Not Verified	365xx
8	125830	3221189	False	NaN	AL	275000.0	Individual	Borrower added on 01/29/13 > New refrigerator and oven.<br>	11.52	Mar-1998	10+ years	GlaxoSmithKline	664.0	660.0	C	MORTGAGE	f	210.36	15.80	Feb-2013	6000.0	7.0	13.0	0.0	0.0	major_purchase	51680.0	95.9	C3	36 months	Major purchase	45.0	Source Verified	352xx
9	19566	8649956	False	NaN	NC	40266.0	Individual	NaN	9.48	Jul-1988	3 years	NaN	674.0	670.0	D	MORTGAGE	f	308.33	18.55	Nov-2013	12000.0	2.0	6.0	1.0	0.0	debt_consolidation	8967.0	70.1	D2	60 months	Moving forward	15.0	Verified	287xx

Last rows

	df_index	id	Charged off	member_id	addr_state	annual_inc	application_type	desc	dti	earliest_cr_line	emp_length	emp_title	fico_range_high	fico_range_low	grade	home_ownership	initial_list_status	installment	int_rate	issue_d	loan_amnt	mort_acc	open_acc	purpose	revol_bal	revol_util	sub_grade	term	title	total_acc	verification_status	zip_code
107833	57021	6828565	True	NaN	TX	77983.0	Individual	Borrower added on 08/19/13 > I will pay off my vehicle (around $10K) and some of my smaller credit cards. Paying off the vehicle will free up almost the exact amount of the payment for this loan so it will have little effect on my monthly budget. I have excellent payment history as my credit report shows. My job is stable.<br>	15.96	Jul-1997	10+ years	Dept of Air Force	664.0	660.0	C	MORTGAGE	w	445.22	16.78	Aug-2013	18000.0	1.0	19.0	debt_consolidation	28930.0	86.9	C5	60 months	Consolidation Loan	24.0	Verified	764xx
107834	46040	7080854	False	NaN	NY	90000.0	Individual	NaN	9.68	Jun-2000	10+ years	Clifford Chance US LLP	704.0	700.0	A	OWN	w	395.18	8.60	Sep-2013	12500.0	1.0	18.0	debt_consolidation	28626.0	40.3	A4	36 months	Pay Credit Cards	35.0	Not Verified	112xx
107835	21898	8755483	False	NaN	TX	78000.0	Individual	Borrower added on 11/07/13 > To be used to pay off higher interest credit cards. This will lower my monthly payments and still be less than what was being paid as a minimum payment on the credit cards and it will be paid back in only 3 years. This will serve to further my efforts to achieve financial freedom.<br>	28.88	Jun-1994	1 year	Safety Coordinator	694.0	690.0	B	MORTGAGE	f	589.22	10.99	Nov-2013	18000.0	2.0	16.0	debt_consolidation	9661.0	61.5	B2	36 months	Debt consolidation	27.0	Verified	776xx
107836	111823	3808149	False	NaN	TX	24000.0	Individual	Borrower added on 03/20/13 > I am very close to my goal of being debt free! After speaking with a financial counselor for a few months now, I've decided to take this opportunity to pay off all my small debts and be rid of high interests traps. I look forward to improving my credit score even more.<br>	10.90	Aug-2001	6 years	Walmart	729.0	725.0	D	RENT	w	52.26	17.77	Apr-2013	1450.0	0.0	10.0	credit_card	3321.0	15.8	D1	36 months	2nd Loan	41.0	Not Verified	757xx
107837	98494	4526720	True	NaN	PA	90000.0	Individual	NaN	5.57	Oct-2000	7 years	Sysco Foods	679.0	675.0	F	MORTGAGE	w	992.31	23.28	May-2013	35000.0	3.0	8.0	credit_card	16680.0	71.7	F2	60 months	Credit card refinancing	20.0	Verified	190xx
107838	42489	7383041	False	NaN	MA	50000.0	Individual	NaN	25.99	Oct-2002	2 years	Public Defender	669.0	665.0	D	RENT	f	364.29	18.55	Oct-2013	10000.0	0.0	9.0	moving	11441.0	84.7	D2	36 months	Moving Loan	35.0	Not Verified	024xx
107839	43933	7071982	False	NaN	NJ	75000.0	Individual	NaN	12.11	Jun-1987	10+ years	Atlanticare Regional Medical Center	714.0	710.0	C	RENT	w	458.33	16.20	Sep-2013	13000.0	7.0	12.0	credit_card	11949.0	33.9	C4	36 months	consolidate	35.0	Not Verified	082xx
107840	108642	4155147	False	NaN	NJ	36000.0	Individual	Borrower added on 04/01/13 > I have about 13,000 in credit card debt that I've accumulated since I was a student. Paying them off one at a time is a painstaking process that takes too long and is ruining my credit history. I want to consolidate all the cards, pay them all off, and once and for all get rid of my all my debt.<br>	17.80	Oct-2004	3 years	Grinberg & Segal PLLC	674.0	670.0	D	RENT	w	468.49	17.77	Apr-2013	13000.0	0.0	16.0	debt_consolidation	14791.0	70.4	D1	36 months	Credit Card Debt Consolidation	19.0	Not Verified	070xx
107841	47783	7275215	False	NaN	AZ	102000.0	Individual	Borrower added on 09/11/13 > Debt Consolidation. Trying to pay off debt in the shortest amount of time, pay as little interest as possible (CC's were crazy) and keep a good credit score.<br>	9.86	Dec-2001	2 years	Black Box Network Services	714.0	710.0	B	MORTGAGE	f	477.71	12.99	Sep-2013	21000.0	2.0	8.0	debt_consolidation	27631.0	66.9	B4	60 months	Debt consolidation	17.0	Source Verified	850xx
107842	5591	9845931	True	NaN	VA	90000.0	Individual	NaN	14.85	Jul-2004	< 1 year	QA Analyst/Performance Test Engineer	709.0	705.0	D	MORTGAGE	f	456.09	19.22	Dec-2013	17500.0	3.0	18.0	debt_consolidation	24862.0	61.4	D4	60 months	Bill Consolidation	32.0	Verified	201xx

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